压力传感器幅频特性不确定度评定方法研究

本文提出一种压力传感器幅频特性不确定度评定方法。 首先,基于核密度估计法计算压力传感器模型参数的概率密度 分布,采用舍选抽样法生成符合概率密度分布的伪随机数;然后,提出一种自适应蒙特卡洛迭代收敛阈值优化方法,实现最优迭 代次数的准确估计;最后,基于最优迭代次数,采用自适应蒙特卡洛法对压力传感器幅频特性的不确定度进行评定,得到其最优 估计值、标准不确定度和给定置信概率下的不确定度区间。 通过压力传感器幅频特性不确定度评定实验验证本文方法的性能。 实验结果表明,本文方法得到的压力传感器幅频特性不确定度绝对误差的均值和最大值分别为 8. 837×10-5 和 5. 103×10-3,与 蒙特卡洛法(实验次数为 100 000)相比分别降低了大约 55%和 76%,与自适应蒙特卡洛法相比分别降低了大约 67%和 79%,说 明本文方法可以有效地评定压力传感器幅频特性的不确定度。

Study on uncertainty evaluation method of pressure sensor amplitude-frequency characteristics

A method for evaluating the uncertainty of amplitude-frequency characteristics of pressure sensors is proposed. Firstly, the probability density distribution of the pressure sensor model parameters was calculated based on the kernel density estimation method, and the pseudo-random number conforming to the probability density distribution was generated by the acceptance-rejection method. Then, an adaptive Monte Carlo iteration convergence threshold optimization method is proposed to accurately estimate the optimal iteration number. Finally, based on the optimal number of iterations, the adaptive Monte Carlo method is used to evaluate the uncertainty of the amplitude-frequency characteristics of the pressure sensor, and the optimal estimate value, the standard uncertainty and the uncertainty interval under the given confidence probability are obtained. The performance of the proposed method is verified by the uncertainty simulation of the amplitude-frequency characteristics of the pressure sensor. The results show that the mean and maximum absolute errors of the uncertainty evaluation results of the pressure sensor amplitude-frequency characteristics obtained by the proposed method are 8. 837×10 -5 and 5. 103×10 -3 , respectively, reduced by about 55% and 76% compared with Monte Carlo method (100 000 tests), and reduced by about 67% and 79% compared with adaptive Monte Carlo method, respectively, indicating that the proposed method can effectively evaluate the uncertainty of the amplitude-frequency characteristics of pressure sensors.